8 papers
Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent
Sayan Banerjee, Krishnakumar Balasubramanian, Promit Ghosal
We provide finite-particle convergence rates for the Stein Variational Gradient Descent (SVGD) algorithm in the Kernelized Stein Discrepancy () and Wasserstein-2 metr…
Uniform-in-time Propagation-of-Chaos for Stein Variational Gradient Descent
Krishnakumar Balasubramanian, Sayan Banerjee, Anna Korba
We study uniform-in-time propagation-of-chaos for continuous-time Stein Variational Gradient Descent (SVGD). Classical finite-time propagation-of-chaos estimates for mean-field sys…
DRIFT: From Robustness Gaps to Invariance Manifolds for AI-Generated Image Detection
Abhishek Ameta, Sayan Banerjee, Shreyas Pandith +4
The rapid evolution of generative image models challenges existing AI-generated image detectors, particularly in open-world settings with unseen generators. Recent training-free ap…
Geodesic Flow Matching on a Riemannian Degradation Manifold for Blind Image Restoration
Akshay Janardan Bankar, Ankita Chatterjee, Sayan Banerjee +3
Blind image restoration requires recovering clean images from observations corrupted by unknown and potentially mixed degradations. While recent deterministic flow-based methods mo…
Finite-Particle Rates for Regularized Stein Variational Gradient Descent
Ye He, Krishnakumar Balasubramanian, Sayan Banerjee +1
We derive finite-particle rates for the regularized Stein variational gradient descent (R-SVGD) algorithm introduced by He et al. (2024) that corrects the constant-order bias of th…
Rank Based Routing in Large Server Systems under Extreme Congestion
Sayan Banerjee, Amarjit Budhiraja, Eva Loeser
We study parallel queues in an extreme heavy-traffic regime: each server works at rate , while jobs arrive to a dispatcher at rate , with fixed . A…